Ligand Binding Pathways and Conformational Transitions of the HIV Protease

It is important to determine the binding pathways and mechanisms of ligand molecules to target proteins to effectively design therapeutic drugs. Molecular dynamics (MD) is a promising computational tool that allows us to simulate protein–drug binding at an atomistic level. However, the gap between the time scales of current simulations and those of many drug binding processes has limited the usage of conventional MD, which has been reflected in studies of the HIV protease. Here, we have applied a robust enhanced simulation method, Gaussian accelerated molecular dynamics (GaMD), to sample binding pathways of the XK263 ligand and associated protein conformational changes in the HIV protease. During two of 10 independent GaMD simulations performed over 500–2500 ns, the ligand was observed to successfully bind to the protein active site. Although GaMD-derived free energy profiles were not fully converged because of insufficient sampling of the complex system, the simulations still allowed us to identify relatively low-energy intermediate conformational states during binding of the ligand to the HIV protease. Relative to the X-ray crystal structure, the XK263 ligand reached a minimum root-mean-square deviation (RMSD) of 2.26 Å during 2.5 μs of GaMD simulation. In comparison, the ligand RMSD reached a minimum of only ~5.73 Å during an earlier 14 μs conventional MD simulation. This work highlights the enhanced sampling power of the GaMD approach and demonstrates its wide applicability to studies of drug–receptor interactions for the HIV protease and by extension many other target proteins

The Structures Related to AChE Tetramerization

<p>(A) The [WAT]₄PRAD complex structure. (B) The compact tetramer structure. (C) The loose tetramer structure. (D) The [AChE_T]₄–ColQ complex model constructed according to the [WAT]₄PRAD complex structure. Each chain is colored differently (A, blue; B, red; C, gray; D, orange; ColQ, yellow). The catalytic S203 was shown as a green ball model for each AChE subunit, and the cyan surfaces are residues near the peripheral site.</p

The RMSF of the [AChE_T]₄–ColQ Complex as Calculated from the 100 Lowest Frequency Modes

<p>All residues are numbered continuously (chain A: 1–583, B: 584-1166, C: 1167–1749, D: 1750–2332, ColQ: 2333–2379).</p

The Involvement Analysis of the Low-Frequency Modes of the [AChE_T]₄–ColQ Complex

<p>The involvement of the modes was shown for the conformational change to (A) the compact and (B) loose tetramer structures. The cumulative involvement of the modes was shown for (C) the compact and (D) loose tetramer structures.</p

A schematic showing how AutoClickChem mimics the azide-alkyne Huisgen cycloaddition.

<p>A) This cycloaddition combines an alkyne and an azide into a 1,2,3-triazole product. B) As a first step, AutoClickChem fragments the alkyne along its triple bond and the azide along the bond connecting its proximal and medial azide nitrogen atom. C) The fragments are then translated so that atomic “handles” are superimposed on top of the corresponding atoms of a 1,2,3-triazole model. D) Next, the fragments are rotated about the handle atoms in order to minimize the distance between the handle-adjacent atoms and the corresponding atoms on the 1,2,3-triazole model. E) The positioned fragments are then rotated in order to reduce steric hindrance. F) Finally, redundant atoms are deleted, and the fragment and 1,2,3-triazole model atoms are merged into a single final structure.</p

The top-scoring predicted PTP1B ligand (in licorice representation), docked into the receptor active site.

<p>Protein residues that participate in electrostatic interactions are highlighted in yellow. Atoms that participate in receptor-ligand hydrogen bonds are shown in ball-and-stick representation. The aromatic ring of the receptor tyrosine residue that participates in π-π stacking and T-stacking interactions with the ligand is shown in thick licorice representation. The crystallographic pose of a known inhibitor is shown in purple, with key sulfonate moieties shown colored by element in licorice representation. Portions of the protein have been removed to facilitate visualization.</p

To demonstrate the diversity of the compounds generated, fifty azides and fifty alkynes were selected at random and reacted <i>in silico</i> using AutoClickChem.

<p>“logP” refers to the estimated partition coefficient, “PSA” refers to the polar surface area, and “MR” refers to the molar refractivity.</p

How Can Hydrophobic Association Be Enthalpy Driven?

Hydrophobic association is often recognized as being driven by favorable entropic contributions. Here, using explicit solvent molecular dynamics simulations we investigate binding in a model hydrophobic receptor−ligand system which appears, instead, to be driven by enthalpy and opposed by entropy. We use the temperature dependence of the potential of mean force to analyze the thermodynamic contributions along the association coordinate. Relating such contributions to the ongoing changes in system hydration allows us to demonstrate that the overall binding thermodynamics is determined by the expulsion of disorganized water from the receptor cavity. Our model study sheds light on the solvent-induced driving forces for receptor−ligand association of general, transferable relevance for biological systems with poorly hydrated binding sites

The Additional Destabilization from the Two-Protein Removal Case Mapped onto the E. coli Map (Blue Diamonds in Figure 3)

<p>The green proteins are not in contact with any other protein. The peptide THX was placed close to the proteins that influence its binding stability. All interactions are non-local, as the respective proteins are not in proximity.</p

Replica-Exchange Accelerated Molecular Dynamics (REXAMD) Applied to Thermodynamic Integration

Accelerated molecular dynamics (AMD) is an efficient strategy for accelerating the sampling of molecular dynamics simulations, and observable quantities such as free energies derived on the biased AMD potential can be reweighted to yield results consistent with the original, unmodified potential. In conventional AMD the reweighting procedure has an inherent statistical problem in systems with large acceleration, where the points with the largest biases will dominate the reweighted result and reduce the effective number of data points. We propose a replica exchange of various degrees of acceleration (REXAMD) to retain good statistics while achieving enhanced sampling. The REXAMD method is validated and benchmarked on two simple gas-phase model systems, and two different strategies for computing reweighted averages over a simulation are compared